rmusic

principal_neumann (nom_maillage) a routine for implementing the EF P1 Lagrange for the Laplace equation following, with conditions Neumann on the mesh nom_maillage.msh

说明：  RBF为径向基函数，RBF网络把网络看作对未知函数的逼近器。输入信号为正弦信号u(k)=0.35sin(3*pi*t)，采用时间为0.001s,网络隐层神经元个数取m=4，网络结构为输入层2-隐层4-输出1，网络的出事全职取随机值，高斯函数的初始值取Cj=[0.65,0.65]T,B=[1.35,1.35,1.35,1.35]T,网络的学习参数取a=0.07,n=0.9。(RBF is a radial basis function, and RBF network regards the network as an approximator to the unknown function. The input signal is sinusoidal signal u(k)=0.35 sin(3*pi*t), the time is 0.001s, the number of hidden layer neurons is m=4, the network structure is input layer 2-hidden layer 4-output 1, the network accident takes random value full-time, the initial value of Gauss function takes Cj=[0.65, 0.65] T, B=[1.35, 1.35] T, the learning parameters of the network take a=0.07, n=0.9.)

基于矢量向量的神经网络图像边缘检测,有消噪的效果，是图像处理的不错程序(baseed on LVQ net work)

说明：  SINS仿真Matlab程序，对初学者还算全，应该有点用处，虽然比较简单，也省些前期编写的麻烦， 希望能花更多时间研究些专门的有用处的东西。如大家有需要还可增加一些其它内容(SINS Matlab simulation program, for beginners fairly full, should be of some use, although relatively simple, but also save the trouble of some pre-prepared, I hope to spend more time to study some specific useful things. If you need to also increase the number of other elements)

用matlab编的联合处理的程序，是使用和不使用的比较(Joint processing using matlab program, and does not use a comparison)

this is new approach for fuel cell control.it is really helpfull.

DTC synchronous machine

说明：  matlab科学计算继续上传，一共10个章节，由浅入深，几乎包括了绝大部分的科学计算方法以及仿真。本人把部分算法做了优化，更为完善(matlab scientific computing continue to upload, a total 10 chapters, easy-to-digest, almost, including most of the scientific method of calculation and simulation. I have done a part of algorithm optimization, a more perfect)

基于Matlab的高斯混合模型的算法实现，该程序可以实现对图像处理的功能(Matlab based on the Gaussian mixture model algorithm, the program can achieve the functions of image processing)

说明：  Smith原图 可以根据你输入的数据画出相应的Smith图(Smith Original data can be drawn based on your input corresponding Smith chart)